Adaptive Routing Forwarding Strategy Based on Neural Network Algorithm

With the profound changes in global digital media, the focus of Internet users has gradually shifted to how to quickly obtain information without paying attention to where the information is stored. However, the current TCP/IP network protocol architecture cannot adapt to the rapid development of today#39s content applications. In order to adapt to the changes in the Internet, information-centric networking (ICN)has received extensive attention. Besides, the optimization of the user service request scheduling problem is the core issue affecting the performance of the ICN , and it is one of the hot research topics in the ICN network. To solve this problem, this paper proposes an adaptive routing forwarding strategy based on neural network algorithm. Through the modeling of the classic architecture named data networking (NDN) network delay model of ICN network, a neural network algorithm is used to delay prediction, and a forwarding strategy mechanism based on predict delay is designed to innovate in the NDN. The interface information Stat is added to the forwarding information base (FIB) of the network component to implement the dynamic selection of the forwarding routing. In addition, routing dynamic self-adaptation adjustment mechanism and fault rerouting function are designed in consideration of the situation of route congestion and interruption. Simulation results show that this strategy effectively reduces network delay and improves network performance

Research on Green Technology Path of Cold-Chain Distribution of Fresh Products Based on Sustainable Development Goals

In order to meet customers’ demand for freshness and the time window of fresh product distribution, and achieve the sustainable development of the fresh product cold-chain logistics industry, green technology is used to solve the optimization problem of the cold-chain distribution path of a variety of fresh products, taking transportation, refrigeration, and carbon emission cost as the objective functions. A hybrid particle swarm optimization (HPSO) algorithm was designed to solve this problem with the minimum freshness requirement of different kinds of cold-chain distribution. The results show that when the minimum freshness requirement of each fresh product is 75%, the total distribution cost obtained by the hybrid particle swarm optimization algorithm is CNY 4218, and the customer satisfaction is 88.22%. While satisfying the freshness constraint, the results obtained by the particle swarm optimization algorithm reduce the total distribution cost by CNY 362 and improve customer satisfaction by 3.82%. Green technology is beneficial to reduce vehicle pollution emissions and the loss of fresh product resources, thus achieving sustainable development

Black and Odorous Water Detection of Remote Sensing Images Based on Improved Deep Learning

Black and odorous water seriously affects the ecological balance of rivers and the health of people living nearby. Satellite remote sensing technology with its advantages of a large range, long-time series, low cost, and high efficiency, has provided a new area for water quality detection. Much archived remote sensing satellite data can be further processed and used as a data source for black and odorous water detection. In this paper, Gaofen-2 remote sensing data with a spatial resolution of 1 m is leveraged as the data source. To enrich the data source in the northern coastal zone of China, we have built a high-quality remote sensing dataset, called the remote sensing images for black and odorous water detection (RSBD) dataset, which is collected from the Gaofen-2 satellite in Yantai, China. In addition, we propose a network with an encoder-decoder discriminant structure for black and odorous water detection. In the network, an augmented attention module is designed to capture a more comprehensive semantic feature representation. Further, the median balancing loss function is adopted to solve the imbalance issues. Experimental results demonstrate that the network is superior to other state-of-the-art semantic segmentation methods on our dataset

Let the loss impartial: a hierarchical unbiased loss for small object segmentation in high-resolution remote sensing images

ABSTRACTThe progress in optical remote sensing technology presents both a possibility and challenge for small object segmentation task. However, the gap between human vision cognition and machine behavior still poses an inherent constrains to the interpretation of small but key objects in large-scale remote sensing scenes. This paper summarizes this gap as a bias of the machine against small object segmentation task, called scale-induced bias. The scale-induced bias causes the degradation in the performance of conventional remote sensing image segmentation methods. Therefore, this paper applies a straightforward but innovative insight to mitigate the scale-induced bias. Specifically, we propose a universal impartial loss, which leverages the hierarchical approach to alleviate two sub-problems separately. The pixel-level statistical methodology is applied to remove the bias between the background and small objects, and an emendation vector is introduced to alleviate the bias between small object categories. Extensive experiments explicitly manifest that our method is fully compatible with the existing segmentation structures, armed with the hierarchical unbiased loss, these structures will achieve satisfactory improvement. The proposed method is validated on two benchmark remote sensing image datasets, where it achieved a competitive performance and could narrow the gap between the human vision cognition and machine behavior

MicroRNA-378-3p/5p suppresses the migration and invasiveness of oral squamous carcinoma cells by inhibiting KLK4 expression

Distant metastasis frequently occurs in oral squamous cell carcinoma (OSCC) and contributes to the adverse prognosis of OSCC. However, the potential mechanisms have not been clarified yet. This study aimed to evaluate the role of miR-378 in the migration and invasion of OSCC in vitro and in vivo. According to our results, the migration and invasion abilities were increased in miR-378-overexpressing cells, while decreased in miR-378-3p/5p-silencing cells. In addition, overexpression of miR-378 suppressed the expressions and activities of MMP-9 and MMP-2. Epithelial-mesenchymal transition (EMT) was restrained by overexpression of miR-378 as evidenced by increase in E-cadherin expression and decrease in N-cadherin and uPA expression. However, the miR-378-3p/5p knockdown groups had the opposite results. Moreover, kallikrein-related peptidase 4 (KLK4) was confirmed to be a target gene of miR-378. Overexpression of KLK4 reversed miR-378 overexpression-induced decrease in migration and invasion via upregulating MMP-9, MMP-2, and N-cadherin levels, while downregulating E-cadhrin level. Finally, the number of metastasis nodules in the lung tissues of nude mice was reduced by overexpression of miR-378, whereas the metastasis nodule number was raised by miR-378 knockdown. Taken together, our study suggests that miR-378/KLK4 axis is involved in the mechanisms of the migration and invasion of OSCC cells. Targeting miR-378/KLK4 axis may be an effective measure for treating OSCC.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

A Comparative Study of Oncolytic Vaccinia Viruses Harboring Different Marine Lectins in Breast Cancer Cells

Our previous studies demonstrated that arming vaccinia viruses with marine lectins enhanced the antitumor efficacy in several cancer cells. This study aims to compare the efficacy of oncolytic vaccinia viruses harboring Tachypleus tridentatus lectin (oncoVV-TTL), Aphrocallistes vastus lectin (oncoVV-AVL), white-spotted charr lectin (oncoVV-WCL), and Asterina pectinifera lectin (oncoVV-APL) in breast cancer cells (BC). These results indicated that oncoVV-AVL elicited the highest anti-tumor effect, followed by oncoVV-APL, while oncoVV-TTL and oncoVV-WCL had lower effects in BC. Further studies showed that apoptosis and replication may work together to enhance the cytotoxicity of oncoVV-lectins in a cell-type dependent manner. TTL/AVL/APL/WCL may mediate multiple pathways, including ERK, JNK, Hippo, and PI3K pathways, to promote oncoVV replication in MDA-MB-231 cells. In contrast, these pathways did not affect oncoVV-TTL/AVL/APL/WCL replication in MCF-7 cells, suggesting that the mechanisms of recombinant viruses in MCF-7 (ER+, PR+) and MDA-MB-231 (TNBC) cells were significantly different. Based on this study, we hypothesized that ER or PR may be responsible for the differences in promoting viral replication and inducing apoptosis between MCF-7 and MDA-MB-231 cells, but the specific mechanism needs to be further explored. In addition, small-molecule drugs targeting key cellular signaling pathways, including MAPK, PI3K/Akt, and Hippo, could be conjunction with oncoVV-AVL to promote breast cancer therapy, and key pathway factors in the JNK and PI3K pathways may be related to the efficacy of oncoVV-APL/TTL/WCL. This study provides a basis for applying oncolytic vaccinia virus in breast carcinoma

Additional file 1 of Single-sEV profiling identifies the TACSTD2 + sEV subpopulation as a factor of tumor susceptibility in the elderly

Supplementary Material

Light Management with Nanostructures for Optoelectronic Devices

Light management is of paramount importance to improve the performance of optoelectronic devices including photodetectors, solar cells, and light-emitting diodes. Extensive studies have shown that the efficiency of these optoelectronic devices largely depends on the device structural design. In the case of solar cells, three-dimensional (3-D) nanostructures can remarkably improve device energy conversion efficiency via various light-trapping mechanisms, and a number of nanostructures were fabricated and exhibited tremendous potential for highly efficient photovoltaics. Meanwhile, these optical absorption enhancement schemes can benefit photodetectors by achieving higher quantum efficiency and photon extraction efficiency. On the other hand, low extraction efficiency of a photon from the emissive layer to outside often puts a constraint on the external quantum efficiency (EQE) of LEDs. In this regard, different designs of device configuration based on nanostructured materials such as nanoparticles and nanotextures were developed to improve the out-coupling efficiency of photons in LEDs under various frameworks such as waveguides, plasmonic theory, and so forth. In this Perspective, we aim to provide a comprehensive review of the recent progress of research on various light management nanostructures and their potency to improve performance of optoelectronic devices including photodetectors, solar cells, and LEDs